Regression analysis is a quantitative tool that is easy to use and can provide valuable information on financial analysis and forecasting.

The simplest form of regression in Python is, well, simple linear regression. With simple linear regression, you're trying to ...

The purpose of this tutorial is to continue our exploration of regression by constructing linear models with two or more explanatory variables. This is an extension of Lesson 9.

Multiple linear regression. Multiple linear regression models are much more complicated and can work with a greater number of lines and shapes on charts.

Learn the difference between linear regression and multiple regression and how investors can use these types of statistical analysis.

Linear regression forecasting is a time-series method that uses basic statistics to project future values for a target variable.

Regression is a statistical method that allows us to look at the relationship between two variables, while holding other factors equal.

When multiple variables are associated with a response, the interpretation of a prediction equation is seldom simple.

The statistical literature and folklore contain many methods for handling missing explanatory variable data in multiple linear regression. One such approach is to incorporate into the regression model ...

Leo A. Goodman, A Modified Multiple Regression Approach to the Analysis of Dichotomous Variables, American Sociological Review, Vol. 37, No. 1 (Feb., 1972), pp. 28-46 ...